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Influence of global navigation satellite system errors in positioning inventory plots for treeheight distribution studies. / Mauro, F.; Valbuena, R.; Manzanera, J.A. et al.
In: Canadian Journal of Forest Research, Vol. 41, No. 1, 2011, p. 11-23.

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Mauro, F, Valbuena, R, Manzanera, JA & García-Abril, A 2011, 'Influence of global navigation satellite system errors in positioning inventory plots for treeheight distribution studies', Canadian Journal of Forest Research, vol. 41, no. 1, pp. 11-23. https://doi.org/10.1139/X10-164

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Mauro F, Valbuena R, Manzanera JA, García-Abril A. Influence of global navigation satellite system errors in positioning inventory plots for treeheight distribution studies. Canadian Journal of Forest Research. 2011;41(1):11-23. doi: 10.1139/X10-164

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Mauro, F. ; Valbuena, R. ; Manzanera, J.A. et al. / Influence of global navigation satellite system errors in positioning inventory plots for treeheight distribution studies. In: Canadian Journal of Forest Research. 2011 ; Vol. 41, No. 1. pp. 11-23.

RIS

TY - JOUR

T1 - Influence of global navigation satellite system errors in positioning inventory plots for treeheight distribution studies

AU - Mauro, F.

AU - Valbuena, R.

AU - Manzanera, J.A.

AU - García-Abril, A.

PY - 2011

Y1 - 2011

N2 - Validation of predictive models in remote sensing requires a good coregistration of field and sensor data sets. However, previous research has demonstrated that Global Navigation Satellite System survey techniques often produce large positioning errors when applied to areas under forest canopies. In this article, we present a repeatable methodology for analyzing the effect of such errors when validating models that predict tree-height distributions from LiDAR data sets. The method is based on conditional probability theory applied to error positioning and includes an error assessment of the surveying technique. A technical criterion for selecting the plot radius that avoids significant effects of positioning errors was proposed. We demonstrated that for a plot radius greater than 10 m, the effects of positioning errors introduced by a phase-differential device were insignificant when studying forest tree-height distributions.

AB - Validation of predictive models in remote sensing requires a good coregistration of field and sensor data sets. However, previous research has demonstrated that Global Navigation Satellite System survey techniques often produce large positioning errors when applied to areas under forest canopies. In this article, we present a repeatable methodology for analyzing the effect of such errors when validating models that predict tree-height distributions from LiDAR data sets. The method is based on conditional probability theory applied to error positioning and includes an error assessment of the surveying technique. A technical criterion for selecting the plot radius that avoids significant effects of positioning errors was proposed. We demonstrated that for a plot radius greater than 10 m, the effects of positioning errors introduced by a phase-differential device were insignificant when studying forest tree-height distributions.

U2 - 10.1139/X10-164

DO - 10.1139/X10-164

M3 - Erthygl

VL - 41

SP - 11

EP - 23

JO - Canadian Journal of Forest Research

JF - Canadian Journal of Forest Research

SN - 0045-5067

IS - 1

ER -